CN111932509B - Pipeline inner surface defect positioning method based on positron annihilation detection technology - Google Patents
Pipeline inner surface defect positioning method based on positron annihilation detection technology Download PDFInfo
- Publication number
- CN111932509B CN111932509B CN202010766082.6A CN202010766082A CN111932509B CN 111932509 B CN111932509 B CN 111932509B CN 202010766082 A CN202010766082 A CN 202010766082A CN 111932509 B CN111932509 B CN 111932509B
- Authority
- CN
- China
- Prior art keywords
- marker
- coordinates
- slice
- center
- defect
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 230000007547 defect Effects 0.000 title claims abstract description 41
- 238000001514 detection method Methods 0.000 title claims abstract description 35
- 238000000034 method Methods 0.000 title claims abstract description 13
- 238000005516 engineering process Methods 0.000 title claims abstract description 12
- 239000003550 marker Substances 0.000 claims abstract description 63
- 238000010586 diagram Methods 0.000 claims abstract description 25
- 239000007788 liquid Substances 0.000 claims abstract description 10
- 238000003708 edge detection Methods 0.000 claims abstract description 4
- 238000007781 pre-processing Methods 0.000 claims abstract description 4
- 230000006798 recombination Effects 0.000 claims abstract description 4
- 238000005215 recombination Methods 0.000 claims abstract description 4
- 238000003384 imaging method Methods 0.000 claims description 26
- 230000002950 deficient Effects 0.000 claims description 10
- 230000002159 abnormal effect Effects 0.000 claims description 4
- 238000012935 Averaging Methods 0.000 claims 1
- 230000000694 effects Effects 0.000 description 4
- 238000012545 processing Methods 0.000 description 4
- 238000013461 design Methods 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 239000000523 sample Substances 0.000 description 2
- 230000009466 transformation Effects 0.000 description 2
- 230000003872 anastomosis Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 239000008240 homogeneous mixture Substances 0.000 description 1
- 230000004807 localization Effects 0.000 description 1
- 239000011159 matrix material Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000009659 non-destructive testing Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N23/00—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/13—Edge detection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/30—Determination of transform parameters for the alignment of images, i.e. image registration
- G06T7/33—Determination of transform parameters for the alignment of images, i.e. image registration using feature-based methods
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
- G06T7/62—Analysis of geometric attributes of area, perimeter, diameter or volume
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
- G06T7/66—Analysis of geometric attributes of image moments or centre of gravity
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/70—Determining position or orientation of objects or cameras
- G06T7/73—Determining position or orientation of objects or cameras using feature-based methods
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10072—Tomographic images
- G06T2207/10104—Positron emission tomography [PET]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E30/00—Energy generation of nuclear origin
- Y02E30/30—Nuclear fission reactors
Abstract
The invention discloses a pipeline inner surface defect positioning method based on positron annihilation detection technology. Injecting the positron mixed liquid into a detected pipeline, injecting the positron mixed liquid into a marker, and placing the marker at a designated position; the PET detection ring performs data acquisition, and a sequence slice diagram is obtained through data recombination and image reconstruction; preprocessing each slice diagram, including edge detection; determining the spatial coordinates of the marker center; determining the space coordinates of the defect area; and calculating the phase position of the defect area and the center of the marker, and further obtaining the actual position of the defect area. The invention uses the marker as the reference point, and the reference point is used for realizing the spatial positioning of the pipeline defect, so that the accurate defect position can be obtained, and the defect that the pipeline is detected by using the positron annihilation technology at present is overcome.
Description
Technical Field
The invention belongs to the field of positron detection, and particularly relates to a method for positioning defects on the inner surface of a pipeline.
Background
The positron annihilation technology is a new nondestructive testing technology for detecting defects of industrial pipelines. For an industrial pipeline to be detected, injecting uniform positron mixed liquid into a pipeline cavity to be detected, detecting by using PET equipment, obtaining a plurality of serial slices distributed in the pipeline cavity to be detected by the positron mixed liquid, and displaying the serial slices as three-dimensional images by using a ray projection method, wherein whether defects appear on the inner surface of the industrial pipeline to be detected can be intuitively seen through the three-dimensional images, but the positions of the defects in space cannot be determined, and the defects are required to be compared with CAD models of the industrial workpiece to be detected, so that a defect positioning means is required. However, due to the specificity of the pipeline, which is generally cylindrical, the existing registration algorithm only can ensure axial registration for the registration of the pipeline model, and cannot ensure the anastomosis of radial angles. Therefore, the existing positron annihilation technology has poor defect localization effect on pipeline detection.
Disclosure of Invention
In order to solve the technical problems mentioned in the background art, the invention provides a pipeline inner surface defect positioning method based on positron annihilation detection technology.
In order to achieve the technical purpose, the technical scheme of the invention is as follows:
a pipeline inner surface defect positioning method based on positron annihilation detection technology comprises the following steps:
(1) Injecting the positron mixed liquid into a detected pipeline, injecting the positron mixed liquid into a marker, and placing the marker at a designated position;
(2) The PET detection ring performs data acquisition, and a sequence slice diagram is obtained through data recombination and image reconstruction;
(3) Preprocessing each slice obtained in the step (2), including edge detection;
(4) Determining the spatial coordinates of the marker center;
(5) Determining the space coordinates of the defect area;
(6) And calculating the phase position of the defect area and the center of the marker, and further obtaining the actual position of the defect area.
Further, the marker is spherical, the inside of the marker is hollow, and the surface of the marker is provided with small holes.
Further, the marker is placed at the edge of the effective imaging view field of the PET detection ring and the circular imaging edge of the central section of the marker is ensured to be inscribed in the imaging view field of the PET detection ring; while the marker is located at the axial center of the PET detector ring.
Further, in step (4), all the slice images are traversed, the object theoretical region is marked on the slice images by a frame of prior information, when an image exists in the region, the positions of all the pixels existing in the region are recorded, the first row and the first column of the slice images are taken as the original points, the row number and the column number of the slice images are respectively marked as x coordinates and y coordinates, the serial number of the slice images is taken as z coordinates, after all the slice images are traversed, all the obtained coordinates are averaged, and the average value is marked as the space coordinates of the center of the marker.
Further, in step (5), a two-dimensional image is generated by taking the inner diameter D of the measured pipeline as a parameter, the two-dimensional image is a circle by taking the center coordinate of the slice diagram as the center coordinate and the inner diameter D of the measured pipeline as the diameter, the two-dimensional image is respectively two-dimensionally registered with the edge images of the slice diagrams, points which do not belong to the circle are abnormal points, the position coordinates of the abnormal points on each slice diagram are recorded, the position coordinates take the first row and the first column of the slice diagram as the origin, the row number and the column number are respectively marked as the x coordinate and the y coordinate, the serial number of the slice diagram is marked as the z coordinate, and the operation is performed on all the slice diagrams to obtain the set of the space coordinates of the defect region.
Further, in step (6), the difference between all the spatial coordinates of the defective area and the spatial coordinates of the marker center is calculated, resulting in the relative position of the defective area and the marker center.
The beneficial effects brought by adopting the technical scheme are that:
according to the invention, the reference position is provided for model registration by using an external marking method, and the detection image with the marking is registered with the model after being processed, so that the problem of radial angle deviation caused by lack of features in pipeline registration can be solved, thereby obtaining an accurate defect position and making up the defect that the pipeline is detected by using the positron annihilation technology at present.
Drawings
FIG. 1 is a flow chart of the method of the present invention;
FIG. 2 is a schematic illustration of the appearance of a marker of the present invention;
FIG. 3 is a schematic illustration of the placement of markers in a collection of detection rings in accordance with the present invention;
FIG. 4 is a three-dimensional view of the spatial location of a marker in the present invention;
FIG. 5 is a diagram of a frame for image registration employed in the present invention;
FIG. 6 is a schematic diagram of an image registration process in accordance with the present invention;
FIG. 7 is a schematic view of the spatial location of a defective area according to the present invention.
Description of the reference numerals: 1. a marker; 2. a marker scaffold; 3. a detection ring; 4. a marker; 5. a pipeline to be tested; 6. detecting an effective field of view of the ring; 7. a detection ring; 8. a marker center; 9. the spatial distance from the marker to each point of the defect edge; 10. a defective region; 11. defect free region boundaries.
Detailed Description
The technical scheme of the present invention will be described in detail below with reference to the accompanying drawings.
The invention designs a pipeline inner surface defect positioning method based on positron annihilation detection technology, which comprises the following steps as shown in fig. 1:
step 1: injecting the positron mixed liquid into a detected pipeline, injecting the positron mixed liquid into a marker, and placing the marker at a designated position;
step 2: the PET detection ring performs data acquisition, and a sequence slice diagram is obtained through data recombination and image reconstruction;
step 3: preprocessing each slice obtained in the step 2, including edge detection;
step 4: determining the spatial coordinates of the marker center;
step 5: determining the space coordinates of the defect area;
step 6: and calculating the phase position of the defect area and the center of the marker, and further obtaining the actual position of the defect area.
In this embodiment, as shown in fig. 2, in order to facilitate the later image processing, the marker is designed to be spherical, the imaging area of the marker on the slice is circular, and the center point of the marker can be accurately obtained by calculating the coordinate mean value of all the pixel points in the area, and the center point is taken as the reference point. The marker is designed as a hollow sphere with an opening at the top for infusing a homogeneous mixture of positron-bearing nuclides for imaging. In order not to affect the imaging quality, the marker should be made of plastic or other materials that do not affect the imaging quality. Furthermore, the thinner the wall thickness should be, the better. The volume of the marker should be small enough so that the marker does not affect the imaging of the conduit being examined, and also, for ease of image processing, the marker should not be too small, otherwise the imaging effect is poor. In summary, the diameter of the spherical marker is designed to be 2cm, the diameter of the top opening is 4mm, the wall thickness is set to be 1mm, and the plastic is selected as the material.
The placement of the tag is shown in figures 3 and 4. FIG. 3 is a schematic diagram of the placement of a marker model within a probe ring, where 1 is the marker, 2 is the marker scaffold, and 3 is the probe ring. Fig. 4 is a three-view of the position of the marker in space, wherein 4 represents the marker, 5 represents the conduit to be detected, 6 represents the effective field of view of the detection ring, and 7 represents the detection ring. In consideration of scattering, the marker is placed as far away from the detected pipeline as possible, so that the detection of the detected pipeline cannot be interfered, and the space of the detected pipeline cannot be occupied. Considering that the effective imaging field of view of a PET detector is about 60-70% of the plane of the detection ring, the marker should be in this effective field of view so as to be able to be detected. Because the imaging field of view is circular in axial section, the marker center section imaging is also circular, therefore, the marker is placed at the edge of the effective imaging field of view, and the circular imaging edge of the marker center section is ensured to be inscribed in the detector imaging field of view. Furthermore, in the axial direction of the detection ring, the marker should be in the axial center position of the detection ring in consideration of the edge effect, which enables the best imaging effect.
In order to design a general algorithm for extracting defective areas, the spatial position of the marker should be fixed, so that the marker is placed on the support, ensuring the position is fixed, and at the same time, the marker is easy to take and place. Because the marker is fixed in position, a group of detection is performed to calibrate the center point of the marker in the image, and only positron nuclides are infused into the marker for imaging, so that the imaging position of the marker is determined.
In this example, the spatial coordinates of the marker center are determined:
the position of the marker on the slice diagram is known according to the prior condition, the theoretical area occupied by the marker is framed by taking the position as the center, the area is a square area on a plurality of slices, the side length is L, in order to prevent the marker position from fluctuating by a small extent, the range is expanded based on the theoretical area, the theoretical area is expanded by 10% in the positive and negative directions of X and Y respectively, namely, a square area with the side length of 1.2L is finally determined, the position of the pixel of the first row and the first column of the slice diagram is taken as the origin, the row number and the column number of the pixel are respectively X and Y, the serial number of the slice diagram is z, the coordinates of all the pixels existing are recorded in the area, and the coordinates are recorded as P { P } 1 ,p 2 ,p 3 … …, assuming that a total of k points are recorded, the spatial coordinates of the marker center, O c (x o ,y o ,z o ) As shown in formula (1):
in this embodiment, the spatial coordinates of the defective area are determined:
the diameter D mm of the detected pipeline can obtain the theoretical size of the pipeline on the imaging image according to the prior condition of the pixel occupied by the actual size on the imaging image, and the pixel occupied by 1mm on the imaging image is recorded as K pixels, so that the pixel size K occupied by the pipeline with the diameter D on the imaging image is recorded as K x D pixels, theoretical detection imaging can be constructed by utilizing the value, namely, the center of the image is taken as a circle center, the positions of the pixels with the distance K from the center are marked, the pixel values of the positions are set to be 1, the pixel values of the other positions are set to be 0, and finally, the edge image of the theoretical detection image is generated, and the image is a binary image.
In the field of image processing, two-dimensional images can be registered, so that the two images are overlapped, and the difference of the two images is conveniently compared. In general, image registration requires a reference image and an image to be registered, as shown in fig. 5, where the reference image is s (x), and the image to be registered is t (x), where x represents a position in N-dimensional space, and in the present invention, N is 2, and represents a position in two-dimensional space. The two images are registered through a transformation matrix T (x), and a transformation formula is shown as a formula (2):
s(x)＝T(x)t(x) (2)
and comparing the transformed error with a set threshold value, judging whether the registration meets the requirement, and iterating again when the registration error is larger than the threshold value until the error is smaller than the threshold value, and outputting a final registration result.
In the present invention, the target image is an actual detection image, the image to be registered is the theoretical detection image constructed above, and as shown in fig. 6, the edge image of the actual detection image and the generated theoretical detection image are registered by using a two-dimensional image rigid registration method. And performing exclusive OR operation on the two images to obtain areas with deviations, recording coordinates of points with the deviations, specifically, taking a first row and a first column of a slice diagram as an origin, respectively marking row numbers and column numbers of the points with the deviations as x coordinates and y coordinates, and taking serial numbers of the slices as z coordinates. Processing all the sequence images to obtain a set T { x } of coordinates of all the defect areas ti ,y ti ,z ti }。
In the present embodiment, the actual position of the defective area is determined:
the center point of the marker is marked as (x) o ,y o ,z o ) The defective area is marked as (x) i ,y i ,z i ) As shown in fig. 7, the pixel difference in the direction X, Y, Z from the marker center in the region where the defect is located can be obtained:
Δx＝x i -x o (3)
Δy＝y i -y o (4)
Δz＝z i -z o (5)
then the actual distance of the defect area in real space relative to the marker can be obtained from k pixels occupied by the actual size as:
x d ＝Δx×k (6)
y d ＝Δy×k (7)
z d ＝Δz×k (8)
and calculating the coordinates of all the areas with defects, so that the real distance between the defect areas and the markers can be obtained, and the purpose of determining the defect areas on the inner wall of the pipeline is achieved.
The embodiments are only for illustrating the technical idea of the present invention, and the protection scope of the present invention is not limited by the embodiments, and any modification made on the basis of the technical scheme according to the technical idea of the present invention falls within the protection scope of the present invention.
Claims (1)
1. The pipeline inner surface defect positioning method based on the positron annihilation detection technology is characterized by comprising the following steps of:
(1) Injecting the positron mixed liquid into a detected pipeline, injecting the positron mixed liquid into a marker, and placing the marker at a designated position;
(2) The PET detection ring performs data acquisition, and a sequence slice diagram is obtained through data recombination and image reconstruction;
(3) Preprocessing each slice obtained in the step (2), including edge detection;
(4) Determining the spatial coordinates of the marker center;
(5) Determining the space coordinates of the defect area;
(6) Calculating the phase position of the defect area and the center of the marker, and further obtaining the actual position of the defect area;
the marker is spherical, the inside of the marker is hollow, and the surface of the marker is provided with small holes;
the marker is placed at the edge of the effective imaging view field of the PET detection ring and ensures that the circular imaging edge of the central section of the marker is inscribed in the imaging view field of the PET detection ring; meanwhile, the marker is positioned at the axial center of the PET detection ring;
in the step (4), traversing all the slice images, marking a theoretical region of a object on a frame of the slice images by prior information, recording the positions of all the pixels existing in the region when the region exists in the image, marking the first row and the first column of the slice images as an origin, respectively marking the row number and the column number as x coordinates and y coordinates, marking the serial number of the slice images as z coordinates, averaging all the obtained coordinates after traversing all the slice images, and marking the average value as the space coordinates of the center of the marker;
in the step (5), taking the inner diameter D of the detected pipeline as a parameter, generating a two-dimensional image, wherein the two-dimensional image takes the center coordinate of a slice diagram as a circle center coordinate, the inner diameter D of the detected pipeline as a diameter as a circle, respectively carrying out two-dimensional registration on the two-dimensional image and the edge image of each slice diagram, taking points which do not belong to the circle as abnormal points, recording the position coordinates of the abnormal points on each slice diagram, wherein the position coordinates take the first row and the first column of the slice diagram as an original point, the row number and the column number of the slice diagram are respectively marked as an x coordinate and a y coordinate, the serial number of the slice diagram is marked as a z coordinate, and executing the operation on all the slice diagrams to obtain a set of space coordinates of a defect region;
in step (6), the difference between all the spatial coordinates of the defective area and the spatial coordinates of the marker center is calculated to obtain the relative position of the defective area and the marker center.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010766082.6A CN111932509B (en) | 2020-08-03 | 2020-08-03 | Pipeline inner surface defect positioning method based on positron annihilation detection technology |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010766082.6A CN111932509B (en) | 2020-08-03 | 2020-08-03 | Pipeline inner surface defect positioning method based on positron annihilation detection technology |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111932509A CN111932509A (en) | 2020-11-13 |
| CN111932509B true CN111932509B (en) | 2024-04-12 |
Family
ID=73306296
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010766082.6A Active CN111932509B (en) | 2020-08-03 | 2020-08-03 | Pipeline inner surface defect positioning method based on positron annihilation detection technology |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111932509B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113687404A (en) * | 2021-08-19 | 2021-11-23 | 南京航空航天大学 | A kind of18F-labeled aerosolised positron imaging agent and preparation method thereof |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105158278A (en) * | 2015-09-01 | 2015-12-16 | 南京航空航天大学 | Nondestructive testing system and method for positioning chamber inner wall defect through positron probe |
| CN109452950A (en) * | 2018-12-29 | 2019-03-12 | 上海联影医疗科技有限公司 | A kind of geometric markers method of die body and imaging device |
| CN109658390A (en) * | 2018-12-04 | 2019-04-19 | 南京航空航天大学 | A kind of area-of-interest exacting method detecting sinusoidal matrix diagram for positive electron |
| CN111080582A (en) * | 2019-12-02 | 2020-04-28 | 易思维（杭州）科技有限公司 | Method for detecting defects on inner surface and outer surface of workpiece |
-
2020
- 2020-08-03 CN CN202010766082.6A patent/CN111932509B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105158278A (en) * | 2015-09-01 | 2015-12-16 | 南京航空航天大学 | Nondestructive testing system and method for positioning chamber inner wall defect through positron probe |
| CN109658390A (en) * | 2018-12-04 | 2019-04-19 | 南京航空航天大学 | A kind of area-of-interest exacting method detecting sinusoidal matrix diagram for positive electron |
| CN109452950A (en) * | 2018-12-29 | 2019-03-12 | 上海联影医疗科技有限公司 | A kind of geometric markers method of die body and imaging device |
| CN111080582A (en) * | 2019-12-02 | 2020-04-28 | 易思维（杭州）科技有限公司 | Method for detecting defects on inner surface and outer surface of workpiece |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111932509A (en) | 2020-11-13 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106667512B (en) | Geometric correction method of X-ray imaging device and breast tomography device | |
| CN105849537B (en) | Calibration device and computed tomography method | |
| US10825165B2 (en) | Inspection method for a manufactured article and system for performing same | |
| WO2018218611A1 (en) | Geometric parameter determination method for cone beam computed tomography system | |
| US11478214B2 (en) | Geometric calibration for cone beam CT using line fiducials | |
| JP2008116373A (en) | Position and attitude-measuring method and instrument | |
| CN105023251B (en) | A kind of geometric correction method of high-resolution cone-beam CT system | |
| US20110150306A1 (en) | Apparatus and methods for determining a boundary of an object for positron emission tomography scatter correction | |
| CN111932509B (en) | Pipeline inner surface defect positioning method based on positron annihilation detection technology | |
| CN101341395A (en) | Computerized topography system and method | |
| EP2679989A2 (en) | X-ray CT system for measuring three dimensional shapes and measuring method of three dimensional shapes by X-ray CT system | |
| CA3020520A1 (en) | Table top image calibration phantom | |
| CN103218834A (en) | Industrial computed tomography (CT) image reconstruction centralized positioning method based on point spread function | |
| Reinhart | Industrial computer tomography–A universal inspection tool | |
| CN110495899A (en) | The method for determining the method and apparatus of geometry calibration and determining associated data | |
| CN109100369B (en) | Defect detection positioning characterization method for cylindrical combined workpiece | |
| Kang et al. | Geometric qualification for robot CT with flexible trajectories | |
| US20230126979A1 (en) | Method and device for detecting thicknesses of coating layers of nuclear fuel particles | |
| CN112308890B (en) | Standard ball-assisted reliable registration method for industrial CT measurement coordinate system | |
| JP5465299B2 (en) | Information processing apparatus and information processing method | |
| Duan et al. | Knowledge-based self-calibration method of calibration phantom by and for accurate robot-based CT imaging systems | |
| Yimin et al. | A novel approach to sub-pixel corner detection of the grid in camera calibration | |
| CN109976322A (en) | A kind of automatic positioning method for realizing carrier loader in restricted clearance | |
| CN104376587B (en) | A kind of loop heat pipe evaporator based on industry CT detection assembles quality evaluating method | |
| US20190146106A1 (en) | Geometric calibration of x-ray imaging systems |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |